"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a				={
    'configuration_electra': ['ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ElectraConfig', 'ElectraOnnxConfig'],
    'tokenization_electra': ['ElectraTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=['ElectraTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=[
	    'ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'ElectraForCausalLM',
	    'ElectraForMaskedLM',
	    'ElectraForMultipleChoice',
	    'ElectraForPreTraining',
	    'ElectraForQuestionAnswering',
	    'ElectraForSequenceClassification',
	    'ElectraForTokenClassification',
	    'ElectraModel',
	    'ElectraPreTrainedModel',
	    'load_tf_weights_in_electra',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=[
	    'TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFElectraForMaskedLM',
	    'TFElectraForMultipleChoice',
	    'TFElectraForPreTraining',
	    'TFElectraForQuestionAnswering',
	    'TFElectraForSequenceClassification',
	    'TFElectraForTokenClassification',
	    'TFElectraModel',
	    'TFElectraPreTrainedModel',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a				=[
	    'FlaxElectraForCausalLM',
	    'FlaxElectraForMaskedLM',
	    'FlaxElectraForMultipleChoice',
	    'FlaxElectraForPreTraining',
	    'FlaxElectraForQuestionAnswering',
	    'FlaxElectraForSequenceClassification',
	    'FlaxElectraForTokenClassification',
	    'FlaxElectraModel',
	    'FlaxElectraPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
	from .tokenization_electra import ElectraTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_electra_fast import ElectraTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_electra import (
		    ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ElectraForCausalLM,
		    ElectraForMaskedLM,
		    ElectraForMultipleChoice,
		    ElectraForPreTraining,
		    ElectraForQuestionAnswering,
		    ElectraForSequenceClassification,
		    ElectraForTokenClassification,
		    ElectraModel,
		    ElectraPreTrainedModel,
		    load_tf_weights_in_electra,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_electra import (
		    TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFElectraForMaskedLM,
		    TFElectraForMultipleChoice,
		    TFElectraForPreTraining,
		    TFElectraForQuestionAnswering,
		    TFElectraForSequenceClassification,
		    TFElectraForTokenClassification,
		    TFElectraModel,
		    TFElectraPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_electra import (
		    FlaxElectraForCausalLM,
		    FlaxElectraForMaskedLM,
		    FlaxElectraForMultipleChoice,
		    FlaxElectraForPreTraining,
		    FlaxElectraForQuestionAnswering,
		    FlaxElectraForSequenceClassification,
		    FlaxElectraForTokenClassification,
		    FlaxElectraModel,
		    FlaxElectraPreTrainedModel,
		)

else:
	import sys

	a				=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



"""simple docstring"""


import os
from distutils.util import strtobool





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase							)				->   Union[str, Any]:




						'''simple docstring'''



						for e in env_keys:
												lowerCamelCase__   =int(os.environ.get(__lowerCAmelCase  ,       -1							)							)
												if val >= 0:
																		return val
						return default





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase=False							)				->   List[str]:




						'''simple docstring'''



						lowerCamelCase__   =os.environ.get(__lowerCAmelCase  ,       str(__lowerCAmelCase							)							)
						return strtobool(__lowerCAmelCase							) == 1  # As its name indicates `strtobool` actually returns an int...





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase="no"							)				->   Union[str, Any]:




						'''simple docstring'''



						lowerCamelCase__   =os.environ.get(__lowerCAmelCase  ,       str(__lowerCAmelCase							)							)
						return value


